Fetaya, Ethan

32 publications

ICLRW 2025 Adversarial Robustness in Parameter-Space Classifiers Tamir Shor, Ethan Fetaya, Chaim Baskin, Alex M. Bronstein

ICML 2025 Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo Idan Achituve, Hai Victor Habi, Amir Rosenfeld, Arnon Netzer, Idit Diamant, Ethan Fetaya

ICML 2024 Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya

ICML 2024 Equivariant Deep Weight Space Alignment Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

ICML 2024 Improved Generalization of Weight Space Networks via Augmentations Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

ICLR 2024 LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya

ICML 2023 Auxiliary Learning as an Asymmetric Bargaining Game Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

NeurIPSW 2023 Data Augmentations in Deep Weight Spaces Aviv Shamsian, David Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan Burghouts, Efstratios Gavves, Cees Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML 2023 Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

UAI 2023 Guided Deep Kernel Learning Idan Achituve, Gal Chechik, Ethan Fetaya

NeurIPS 2022 Functional Ensemble Distillation Coby Penso, Idan Achituve, Ethan Fetaya

ICML 2022 Multi-Task Learning as a Bargaining Game Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

ICLR 2021 Auxiliary Learning by Implicit Differentiation Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

ICML 2021 From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron

ICML 2021 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya

ICLR 2021 Learning the Pareto Front with Hypernetworks Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik

IJCAI 2021 On Learning Sets of Symmetric Elements (Extended Abstract) Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

ICML 2021 Personalized Federated Learning Using Hypernetworks Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik

NeurIPS 2021 Personalized Federated Learning with Gaussian Processes Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya

ICML 2020 On Learning Sets of Symmetric Elements Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

ICLR 2020 Understanding the Limitations of Conditional Generative Models Ethan Fetaya, Jörn-Henrik Jacobsen, Will Grathwohl, Richard Zemel

NeurIPS 2019 Incremental Few-Shot Learning with Attention Attractor Networks Mengye Ren, Renjie Liao, Ethan Fetaya, Richard Zemel

ICML 2019 On the Universality of Invariant Networks Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman

ICLR 2018 Learning Discrete Weights Using the Local Reparameterization Trick Oran Shayer, Dan Levi, Ethan Fetaya

NeurIPS 2018 Neural Guided Constraint Logic Programming for Program Synthesis Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William Byrd, Matthew Might, Raquel Urtasun, Richard Zemel

ICML 2018 Neural Relational Inference for Interacting Systems Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard Zemel

ICML 2018 Reviving and Improving Recurrent Back-Propagation Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard Zemel

ICCVW 2017 Real-Time Category-Based and General Obstacle Detection for Autonomous Driving Noa Garnett, Shai Silberstein, Shaul Oron, Ethan Fetaya, Uri Verner, Ariel Ayash, Vlad Goldner, Rafi Cohen, Kobi Horn, Dan Levi

ECCV 2016 Human Pose Estimation Using Deep Consensus Voting Ita Lifshitz, Ethan Fetaya, Shimon Ullman

AISTATS 2016 Unsupervised Ensemble Learning with Dependent Classifiers Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger

AISTATS 2015 Graph Approximation and Clustering on a Budget Ethan Fetaya, Ohad Shamir, Shimon Ullman

ICML 2015 Learning Local Invariant Mahalanobis Distances Ethan Fetaya, Shimon Ullman